Pottslab
Unsupervised multilabel image segmentation (color/gray/multichannel) based on the Potts model (aka piecewise constant Mumford-Shah model)
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Download Latest Version (.zip)- build_wheels.yml
- convop.m
- linop.m
- radonop.m
- convkernel.m
- countJumps.m
- energyL2Potts.m
- intmatrix.m
- medianw.m
- plimage2double.m
- plpsnr.m
- psnr.m
- randidx.m
- randl.m
- samplesToWeights.m
- segToLabel.m
- setPLJavaPath.m
- showdbl.m
- showPotts.m
- showSparse.m
- softThreshold.m
- spconvmatrix.m
- spdiffmatrix.m
- church.jpg
- colors.png
- desert.jpg
- imageSources.txt
- loadPcwConst.m
- loadSparse.m
- lookmickey.jpg
- demoL1iPotts_DecImp.m
- demoL1iPotts_DecLap.m
- demoL1iSpars_DecImp.m
- demoL1iSpars_DecLap.m
- demoL2iPotts_Deconv.m
- demoL2iPotts_Fourier.m
- demoL2iPotts_Linop.m
- demoL2iSpars_Deconv.m
- demoPotts_GaussianNoise.m
- demoPotts_ImpulsiveNoise.m
- demoPotts_LaplacianNoise.m
- plFigPottsRec7Angles.fig
- demoPotts2DColorDenoising.m
- demoPotts2DColorInpainting.m
- demoPotts2DColorMissing.m
- demoPotts2DColorSegmentation.m
- demoPotts2DRadon.m
- pottsLabDemo.m
- release_smoke_test.ipynb
- noisy.png
- uPottsRho.png
- phantom.png
- recFBP.png
- recFBPRamLak.png
- recPotts.png
- potts1d.png
- texture.png
- titleImage.png
- Benchmark$Thunk.class
- Benchmark.class
- IndexedLinkedHistogram$HistNode.class
- IndexedLinkedHistogram.class
- IndexedLinkedHistogramUnweighted$HistNode.class
- IndexedLinkedHistogramUnweighted.class
- JavaTools.class
- L2Potts.class
- PLImage$1.class
- PLImage.class
- PLProcessor.class
- PLVector.class
- RunMe.class
- MANIFEST.MF
- Benchmark.java
- IndexedLinkedHistogram.java
- IndexedLinkedHistogramUnweighted.java
- JavaTools.java
- L2Potts.java
- PLImage.java
- PLProcessor.java
- PLVector.java
- RunMe.java
- PottsSegmentationJ_.jar
- findBestPartition.m
- iPottsADMM.m
- reconstructionFromPartition.m
- minL1iPotts.m
- minL1Potts.m
- minL2iPotts.m
- minL2Potts.m
- iPotts2DADMM.m
- minL2iPotts2DADMM.m
- minL2Potts2DADMM.m
- __init__.py
- _core.pyi
- _core_py.py
- inverse.py
- potts1d.py
- potts2d.py
- sparsity.py
- tikhonov.py
- utils.py
- iSparsADMM.m
- iSparsByPottsADMM.m
- minSpars.m
- minL1iSpars.m
- minL1Spars.m
- minL2iSpars.m
- minL2Spars.m
- admm.rs
- l1potts.rs
- l2potts.rs
- lib.rs
- processor.rs
- conftest.py
- test_brute_force.py
- test_edge_cases.py
- test_hardening.py
- test_integration.py
- test_inverse.py
- test_l1_median_bug.py
- test_l1_potts_1d.py
- test_l2_potts_1d.py
- test_matlab_parity.py
- test_numerical_precision.py
- test_potts_2d.py
- test_properties.py
- test_sparsity.py
- test_tikhonov.py
- test_utils.py
- minL1Tikhonov.m
- minL2Tikhonov.m
- minL2TikhonovFBP.m
- .gitignore
- benchmark.py
- Cargo.lock
- Cargo.toml
- CHANGELOG.md
- CITATION.cff
- installPottslab.m
- LICENSE
- PORTED_BY.md
- pottslab-standalone.jar
- pyproject.toml
- README.md
- README_PYTHON.md
# Installation Guide
1. Get the code
git clone https://github.com/mstorath/Pottslab
Downloads the entire project code from GitHub to your computer.
cd Pottslab
Moves into the project folder you just downloaded.
2. Official Install Script
Easy RecommendedPrerequisites
- Python 3 Python is required to use pip.
pip install pottslab
Installs the package published on PyPI directly โ no need to clone the source.
After installing, open a new terminal and run the program's version command (e.g. --version) to confirm it worked.
Pulled directly from this repo's README.
3. Python
EasyPrerequisites
pip install pottslab
Installs the package published on PyPI directly โ no need to clone the source.
If it runs without errors and prints output in the terminal, it worked.
Pulled directly from this repo's README.
4. Rust
MediumPrerequisites
- Git Needed to download the project code from GitHub.
- Rust (rustup) Installing via rustup also installs cargo.
cargo build --release
Compiles the Rust project.
cargo run
Builds and then immediately runs the program.
If cargo build finishes without errors, it worked. The executable is created under target/.
// repository documentation
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